Uniform TitleDrowsiness detection while driving using fractal analysis and wavelet transform
NameParikh, Prachi (author), Micheli-Tzanakou, Evangelia (chair), Shoane, George (internal member), Drzeweicki, Gary (internal member), Rutgers University, Graduate School - New Brunswick,
DescriptionThe EEG signal plays a key role as a nondestructive testing method in the diagnosis and functional determination of the brain. EEG recordings represent changes in alertness, arousal, sleep and cognition. Boredom, fatigue and monotony of a task may induce drowsiness that leads to a decrease in alertness. This can have serious consequences in tasks involving constant vigilance and control such as driving. In the current study, EEG signals are recorded using a car simulator and analyzed using Fractal analysis and Wavelet Transform. It is observed that there is an increase in the alpha frequencies in the latter stages of driving indicating a state of drowsiness. The analysis techniques used provide results quickly, which is essential to provide instant feedback.
NoteIncludes bibliographical references (p. 82-87).
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.